Channel estimation in a wireless communication system is needed for coherent demodulation at a receiver, and is also used in multi-antenna systems to increase throughput or coverage using knowledge of the transmitter and/or receiver. Channel estimation is affected by the channel conditions such as signal to interference plus noise ratio (SINR), mobile velocity, and multi-path delay spread.
Typically, channel estimation involves estimating the channel between a transmitter and a receiver based on known pilot symbols. The pilot symbols are transmitted periodically, for example, once per time slot, for each carrier frequency. To estimate the channel for data received between pilot symbols, an interpolation method is used. There exist several interpolation algorithms that may be employed for channel estimation. Of these, first order interpolation algorithms are of particular interest because of their low complexity.
First order interpolation algorithms include, without limitation, averaging algorithms, linear interpolation algorithms, minimum mean square error (MMSE) algorithms, and nearest neighbor algorithms. Of these methods, the MMSE algorithm exhibits the best performance over different channel conditions such as low and high Doppler conditions, different delay spreads, as well as different SINR levels. However, the MMSE algorithm assumes knowledge of the Doppler frequency, which may not be available or easily obtainable.
The averaging algorithm is a good alternative for low Doppler channels, i.e., Doppler channels where the mobile device is traveling at a low speed, as well as for channels with a low SINR, but performance of the averaging algorithm decreases significantly for high Doppler channels. i.e., Doppler channels where the mobile device is traveling at a high speed. The linear interpolation algorithm performs well in high Doppler channels, but is not good for low SINR channels and low Doppler channels. The nearest neighbor algorithm exhibits performance that is between the performance of the linear interpolation algorithms and the performance of the averaging algorithms.
Therefore, what is needed is a channel estimation method that performs well under various channel conditions such as low and high Doppler, low and high SINR, and different delay spreads.